Automatic implement detection and management system

ABSTRACT

A method for operating an agricultural vehicle. The method including capturing, by the at least one image capturing device, image data of the implement and receive, by the controller, the image data of the implement, The method further includes identifying the implement, by the controller, depending at least in part upon the image data of the implement. The method further includes setting, by the controller, at least one operational parameter of the implement, and managing, by the controller, a turning maneuver of the agricultural vehicle depending at least in part upon the image data of the implement.

BACKGROUND OF THE INVENTION

The present invention pertains to agricultural vehicles and, morespecifically, to a system for detecting and managing an implement whichis attached to an agricultural vehicle.

Farmers utilize a wide variety of implements to prepare soil forplanting. For example, a strip tillage implement is capable ofcollectively tilling soil in strips along the intended planting rows,moving residue to the areas in between rows, and preparing the seedbedof the strip in preparation for planting. As another example, a fieldcultivator is capable of simultaneously tilling soil and leveling thetilled soil in preparation for planting.

Some modern implements may automatically identify themselves to thecontrol system of the agricultural vehicle upon being electricallycoupled to the agricultural vehicle, for example by way of an ISOBUSconnection. However, some implements may not include modern electronics.In such cases, the operator must manually identify the implement typewithin the control software of the agricultural vehicle in order toproperly set operational parameters and log implement data. As can beappreciated, the operator may forget to identify or improperly identifythe implement; thus, causing suboptimal operation and improper datacollection. Therewith, the operator or an automatic guidance system mayimproperly conduct a turning maneuver if an implement is improperlyidentified. For instance, the operator or guidance system may conduct anoverly narrow end-of-row turn, which may lead to the implementcontacting the agricultural vehicle. If the contact between theimplement and the agricultural vehicle is severe, then such contact maydamage the implement or the agricultural vehicle

What is needed in the art is a system and method to automaticallyidentify an implement and manage the operation thereof.

SUMMARY OF THE INVENTION

Exemplary embodiments provided according to the present disclosureinclude a method and an agricultural system for the automatic detectionand management of an implement which is towed behind an agriculturalvehicle. The agricultural vehicle automatically detects a type ofimplement, sets the operational parameters, and manages turningmaneuvers based at least in part upon the sensed and real-time positionof the implement relative to the agricultural vehicle.

In some exemplary embodiments provided in accordance with the presentdisclosure, a method for operating an agricultural vehicle is provided.The agricultural vehicle includes a controller and at least one imagecapturing device operably connected to the controller. The agriculturalvehicle tows an implement. The method includes capturing, by the atleast one image capturing device, image data of the implement,receiving, by the controller, the image data of the implement, andidentifying the implement, by the controller, depending at least in partupon the image data of the implement. The method also includes setting,by the controller, at least one operational parameter of the implement,and managing, by the controller, a turning maneuver of the agriculturalvehicle depending at least in part upon the image data of the implement.

In some exemplary embodiments provided in accordance with the presentdisclosure, an agricultural vehicle which is configured to tow animplement is provided. The agricultural vehicle includes a frame and atleast one image capturing device connected to the frame. The at leastone image capturing device is configured to capture image data of theimplement. The agricultural vehicle also includes a controller operablyconnected to the at least one image capturing device. The controller isconfigured to receive the image data of the implement, identify theimplement depending at least in part upon the image data of theimplement, set at least one operational parameter of the implement, andmanage a turning maneuver of the agricultural vehicle depending at leastin part upon the image data of the implement.

One possible advantage that may be realized by exemplary embodimentsprovided according to the present disclosure is that an operator doesnot need to manually identify the type of the implement.

Another possible advantage that may be realized by exemplary embodimentsprovided according to the present disclosure is that turning maneuversmay be optimized, automatically without operator input, by reducing theturning radius to its minimum value without risking damage to theimplement and the agricultural vehicle.

BRIEF DESCRIPTION OF THE DRAWINGS

For the purpose of illustration, there are shown in the drawings certainembodiments of the present invention. It should be understood, however,that the invention is not limited to the precise arrangements,dimensions, and instruments shown. Like numerals indicate like elementsthroughout the drawings. In the drawings:

FIG. 1 illustrates a schematic view of an exemplary embodiment of anagricultural system that includes an autonomous or semi-autonomousagricultural vehicle and an implement;

FIG. 2 illustrates a perspective view of the implement of FIG. 1 whichis connected to the agricultural vehicle, wherein the agriculturalvehicle is shown in schematic form;

FIG. 3 illustrates a perspective view of an end-of-row turning maneuverof the agricultural vehicle; and

FIG. 4 illustrates a flowchart of a method for operating theagricultural vehicle.

DETAILED DESCRIPTION OF THE INVENTION

The terms “forward”, “rearward”, “left” and “right”, when used inconnection with the agricultural vehicle and/or components thereof areusually determined with reference to the direction of forward operativetravel of the towing vehicle, but they should not be construed aslimiting. The terms “longitudinal” and “transverse” are determined withreference to the fore-and-aft direction of the towing vehicle and areequally not to be construed as limiting.

Referring now to the drawings, and more particularly to FIGS. 1-2, thereis shown an autonomous or semi-autonomous agricultural system 10 thatgenerally includes an autonomous or semi-autonomous agricultural vehicle12 and an agricultural implement 14 connected to the agriculturalvehicle 12.

The agricultural vehicle 12 may generally include a frame 16, a primemover, a cab, and wheels and/or tracks 18. It is noted that only therear wheels and/or tracks 18 are illustrated in FIG. 1. The agriculturalvehicle 12 may also include a user interface 20 located within the caband a steering system 22 for steering the agricultural vehicle 12. Theuser interface 20 may include a selection program or picklist whichallows the operator to input a type of the implement 14 as well as theoperational parameters, e.g. implement and/or vehicle settings such astool depth, down pressure, ground speed, etc. The steering system 22 maygenerally include proportional or directional control valves that arehydraulically connected to a steering actuator for steering the wheelsand/or tracks 18 of the agricultural vehicle 12. The agriculturalvehicle 12 may be in the form of any desired agricultural machine, suchas a tractor, which is capable of being fully or at least partiallyautonomously operated.

The agricultural vehicle 12 may also include at least one imagecapturing device 24. The at least one image capturing device 24 maycapture pictures and/or videos of the implement 14 and the areasurrounding the implement 14. The at least one image capturing device 24may collect the image data before the implement 14 has been connected tothe agricultural vehicle 12, during the connection process, and/or afterthe implement 14 has been connected to the agricultural vehicle 12. Forinstance, the image capturing device 24 may continually collect imagedata throughout a farming operation or selectively capture image dataonly during a connection process and a turning maneuver. Each imagecapturing device 24 may be connected to the frame 16. The at least oneimage capturing device 24 may be in the form of a camera, such as abackup camera.

The implement 14 may be pivotally connected to and towed by theagricultural vehicle 12. The implement 14 generally includes a mainframe 26, a subframe 28, wheels connected to the main frame 26, variousground-engaging tools mounted to the frame 26 and/or the subframe 28,and a tongue or drawbar 30 which pivotally connects to the agriculturalvehicle 12. Once connected to the agricultural vehicle 12, thelongitudinal axis LA of the implement 14, e.g. the drawbar 30 thereof,may define an angle A1 relative to a transverse axis TA of theagricultural vehicle 12, e.g. an axis which is perpendicular to theforward direction of travel (FIG. 2). The implement 14 may alsooptionally include at least one identifying characteristic 32. The atleast one identifying characteristic 32 may include a brand name, alogo, a model number, and/or a QR code. The implement 14 may be in theform of any desired ground-engaging implement, such as a fieldcultivator, a disk ripper, a fertilizer applicator implement, or asweep. It should be appreciated that the implement 14 may alsoincorporate a fertilizer device and/or a portion thereof. As can beappreciated, the implement 14 may not include a “smart” electricalconnection which interfaces the agricultural vehicle 12.

The autonomous or semi-autonomous agricultural system 10 may furtherinclude a controller 40 with a memory 42. The controller 40 may beincorporated into the agricultural vehicle 12. The controller 40 can beoperably connected to the user interface 20, the steering system 22, andeach image capturing device 24. The controller 40 may also beadditionally connected to any other desired sensor, including a globalpositioning system (GPS) location sensor, a speed sensor, and/or aninclinometer.

The controller 40 may comprise the Case IH Advanced Farming System®(AFS), which may collectively and automatically control and record theoperation of the agricultural vehicle 12 and the implement 14. Thecontroller 40 may comprise one or more systems for identifying theimplement 14, recording data relating to the agricultural vehicle 12and/or the implement 14, and controlling the operation of theagricultural vehicle 12 and/or the implement 14. Therein, the controller40 may include an automatic vehicle guidance system 44, which activelycontrols the steering system 22, and a data management system 46 forrecording data relating to the agricultural vehicle 12 and/or theimplement 14. Hence, the controller 40 can continually calculate avehicle steering heading or turning maneuver by comparing vehicleposition and directional heading to a desired travel path, and furtherby incorporating a determined minimum turning angle and/or interferencezone Z (FIG. 1). Thereafter, the controller 40 may send the vehiclesteering heading output signal and/or the steer-limit output signal tothe steering system 22, which in turn steers the wheels and/or tracks18. The controller 40 may also comprise one or more communicationinterfaces which may be configured to use standardized protocols forcommunication such as TCP/IP, Bluetooth, CAN protocol and higher-layerprotocols such as HTTP, TLS, and the like.

Additionally, the controller 40 may automatically conduct implementdetection and turn management of the agricultural vehicle 12. Moreparticularly, the controller 40 may receive the image data from theimage capturing device(s) 24, identify the implement 14 depending atleast in part upon the image data, set at least one operationalparameter, and manage a turning maneuver of the agricultural vehicle 12depending at least in part upon the image data. As can be appreciated aturning maneuver may include any desired turning operation of theagricultural vehicle 12, such as an end-of-row turn in the headland areaof the field. For instance, FIG. 3 illustrates the agricultural vehicle12 conducting a left-hand, end-of-row turn along a path P1 wherein theagricultural implement follows along path P2. During the left-handturning maneuver, the left wheel 18 of the agricultural vehicle 12 maybecome too close or contact the drawbar 30 of the implement 12.

In identifying the implement 14, the controller 40 can compare the imagedata collected by the image capturing device 24 to a database ofimplements and match the implement 14 to one implement of the databaseof implements. For instance, the controller 40 may compare one or moreidentifying characteristics of the implement 14, such as brand name orlogo 32, with identifying characteristics of known implements.Therewith, in identifying the implement 14, the controller 40 mayconduct a machine learning algorithm or other deep-learning artificialintelligence algorithm to, at least partially, create the database ofimplements and to identify the implement 14. It should be appreciatedthat the database of implements may comprise information of varioustypes of implements and the identifying characteristics associated withthe various types of implements. Such identifying characteristicinformation may include the brand name, model number, height and/orshape of the frame and/or subframe, QR code(s), accompanying tools, etc.

Additionally, the controller 40 may also streamline the implementselection process within the data management system 46. For instance,the controller 40 may populate a picklist with one or more possibleimplements from which the operator may choose. Also, for instance, thecontroller 40 may automatically select the appropriate implement in thedata management system 46. Thereby, by way of example only, the operatormay initially choose the implement 14 within the data management system46, and the controller may subsequently automatically select theimplement 14 by way of the machine learning algorithm. Thereafter, thecontroller 40 may automatically set the initial settings and/oroperational parameters of the implement 14.

The controller 40 may optimize the turning maneuver by minimizing aturning radius of the agricultural vehicle 12. In managing the turningmaneuver, the controller 40 may also artificially limit a maximumturning angle of the agricultural vehicle 12 to prevent interferencebetween the implement 14 and the agricultural vehicle 12. Furthermore,the controller 40 may determine the angle A1 of the drawbar 30 relativeto the agricultural vehicle 12 depending at least in part upon the imagedata such that the artificial limit of the maximum turning angle of theagricultural vehicle 12 depends upon the real-time angle A1 of thedrawbar relative to the agricultural vehicle 12. It should beappreciated that the controller 40 may also monitor a portion of theagricultural vehicle 12, e.g. the wheels and/or tracks 18, relative tothe position of the drawbar 30. Additionally or alternatively, thecontroller 40 may determine an interference zone Z of the drawbar 30. Ifa portion of the agricultural vehicle 12, e.g. the rear wheels and/ortracks 18, enters or occupies the interference zone Z, it may signifythat a potential interference, i.e., contact, between the agriculturalvehicle 12 and the implement 14 may occur. The controller 40 maydetermine the interference zone Z by defining an area which is apreselected distance away from each side of the drawbar 30. Thereafter,the controller 40 may set the artificial limit of the maximum turningangle of the agricultural vehicle 12 depending upon a position of theagricultural vehicle 12 relative to the interference zone Z of thedrawbar 30. As used herein, the term interference zone refers to an areasurrounding at least a portion of the drawbar 30.

Also, the controller 40 may manage the turning maneuvers by determiningand sending a steer-limit output signal to the steering system 22. Thesteer-limit output signal may correspond to a predetermined minimumangle and/or desired interference zone Z. Upon receiving the outputsignal from the controller 40, the steering system 22 may prevent theagricultural vehicle 12 from turning beyond the maximum turning angle ofthe agricultural vehicle 12 which was artificially limited by thecontroller 40 for a specific implement type.

The controller 40 may also automatically steer the agricultural vehicle12, via the automatic vehicle guidance system 44, during the turningmaneuver. Therein, the controller 40 may automatically control thesteering system 22 to minimize a turning radius of the agriculturalvehicle 12 and prevent interference between the implement 14 and theagricultural vehicle 12.

The autonomous or semi-autonomous agricultural system 10 may alsooptionally include a network 50 which operably couples the agriculturalvehicle 12 to one or more other agricultural vehicles 52. Thereby, theagricultural vehicle 12 can be part of a neural network comprising atleast one other agricultural vehicle 52. The network 50 may operablyconnect the controller 40 to the controllers of the other agriculturalvehicles 52. The network 50 may be configured to receive and transmitthe image data of the implement 14. The network 50 may be any suitablenetwork, including a wireless network having one or more processors ornodes. Additionally, the network 50 may broadly represent anycombination of one or more data communication networks including localarea networks, wide area networks, etc., using a wired or wirelessconnection.

Furthermore, the autonomous or semi-autonomous agricultural system 10may also optionally include a remote machine learning or data center 54.In cooperation with the controller 40, the data center 54 may also beconfigured to receive, process, and record the image data of theimplement 14. Additionally, the data center 54 may include one or moreprocessors arranged to conduct a machine learning algorithm or otherdeep-learning artificial intelligence algorithm to, at least partially,create the database of implements and/or to identify the implement 14.

Referring now to FIG. 4, there is shown a flowchart of a method 60 foroperating the agricultural vehicle 12 of the agricultural system 10. Theat least one image capturing device 24 captures image data of theimplement 14 (at block 62). The controller 40 receives the image dataand identifies the type of the implement 14 (at block 64). Thecontroller 40 and/or the data center 54 may create a database ofimplements and/or update a premade database of implements (at block 66).The controller 40 may automatically select the implement 14 within thedata management system 46 so that the implement data is appropriatelylogged (at block 68). The controller 40 may then set at least oneoperational parameter of the implement, which may include one or moresettings of the implement 14 and/or the agricultural vehicle 12 such astool depth, down pressure, ground speed, etc. (at block 70). Thereafter,the controller 40 may determine the angle A1 of the drawbar 30 relativeto the agricultural vehicle 12 (at block 72) and/or determine theinterference zone Z of the drawbar 30 (at block 74). Thereafter, thecontroller 40 may manage one or more turning maneuvers of theagricultural vehicle 12 (at block 76).

It is to be understood that the steps of the method 60 may be performedby the controller 40 upon loading and executing software code orinstructions which are tangibly stored on a tangible computer readablemedium, such as on a magnetic medium, e.g., a computer hard drive, anoptical medium, e.g., an optical disc, solid-state memory, e.g., flashmemory, or other storage media known in the art. Thus, any of thefunctionality performed by the controller 40 described herein, such asthe method 60, is implemented in software code or instructions which aretangibly stored on a tangible computer readable medium. The controller40 loads the software code or instructions via a direct interface withthe computer readable medium or via a wired and/or wireless network.Upon loading and executing such software code or instructions by thecontroller 40, the controller 40 may perform any of the functionality ofthe controller 40 described herein, including any steps of the method 60described herein.

The term “software code” or “code” used herein may refer to anyinstructions or set of instructions that influence the operation of acomputer or controller. They may exist in a computer-executable form,such as machine code, which is the set of instructions and data directlyexecuted by a computer's central processing unit or by a controller, ahuman-understandable form, such as source code, which may be compiled inorder to be executed by a computer's central processing unit or by acontroller, or an intermediate form, such as object code, which isproduced by a compiler. As used herein, the term “software code” or“code” also includes any human-understandable computer instructions orset of instructions, e.g., a script, that may be executed on the flywith the aid of an interpreter executed by a computer's centralprocessing unit or by a controller.

These and other advantages of the present invention will be apparent tothose skilled in the art from the foregoing specification. Accordingly,it is to be recognized by those skilled in the art that changes ormodifications may be made to the above-described embodiments withoutdeparting from the broad inventive concepts of the invention. It is tobe understood that this invention is not limited to the particularembodiments described herein, but is intended to include all changes andmodifications that are within the scope and spirit of the invention.

1. A method for operating an agricultural vehicle, the agriculturalvehicle comprising a controller and at least one image capturing deviceoperably connected to the controller, the agricultural vehicle towing animplement, the method comprising: capturing, by the at least one imagecapturing device, image data of the implement; receiving, by thecontroller, the image data of the implement; identifying the implement,by the controller, depending at least in part upon the image data of theimplement; setting, by the controller, at least one operationalparameter of the implement; and managing, by the controller, a turningmaneuver of the agricultural vehicle depending at least in part upon theimage data of the implement.
 2. The method of claim 1, wherein managingthe turning maneuver comprises optimizing the turning maneuver byminimizing a turning radius of the agricultural vehicle.
 3. The methodof claim 1, wherein managing the turning maneuver comprises artificiallylimiting a maximum turning angle of the agricultural vehicle to preventinterference between the implement and the agricultural vehicle.
 4. Themethod of claim 3, wherein the implement comprises a drawbar connectedto the agricultural vehicle, wherein the method further comprisesdetermining, by the controller, an angle of the drawbar relative to theagricultural vehicle depending at least in part upon the image data ofthe implement, wherein the controller artificially limits the maximumturning angle of the agricultural vehicle depending upon the angle ofthe drawbar relative to the agricultural vehicle.
 5. The method of claim3, wherein the implement comprises a drawbar connected to theagricultural vehicle, wherein the method further comprises determining,by the controller, an interference zone of the drawbar, wherein thecontroller artificially limits the maximum turning angle of theagricultural vehicle depending upon a position of the agriculturalvehicle relative to the interference zone of the drawbar.
 6. The methodof claim 3, wherein the agricultural vehicle comprises a steering systemoperably connected to the controller, wherein the controller isconfigured to determine and send a steer-limit output signal to thesteering system so that the steering system prevents the agriculturalvehicle from turning beyond the maximum turning angle of theagricultural vehicle which was artificially limited by the controller.7. The method of claim 6, wherein managing the turning maneuvercomprises automatically steering the agricultural vehicle during theturning maneuver by way of the controller automatically controlling thesteering system to minimize a turning radius of the agricultural vehicleand prevent interference between the implement and the agriculturalvehicle.
 8. The method of claim 1, wherein identifying the implementcomprises comparing the image data of the implement to a database ofimplements and matching the implement to one implement of the databaseof implements.
 9. The method of claim 8, wherein the agriculturalvehicle is part of a neural network comprising at least one otheragricultural vehicle, wherein the controller is operably connected to anetwork which operably connects the agricultural vehicle to the at leastone other agricultural.
 10. The method of claim 8, wherein thecontroller is configured to conduct a machine learning algorithm to, atleast partially, create the database of implements and to identify theimplement.
 11. An agricultural vehicle configured to tow an implement,comprising: a frame; at least one image capturing device connected tothe frame, the at least one image capturing device being configured tocapture image data of the implement; and a controller operably connectedto the at least one image capturing device, the controller beingconfigured to: receive the image data of the implement; identify theimplement depending at least in part upon the image data of theimplement; set at least one operational parameter of the implement; andmanage a turning maneuver of the agricultural vehicle depending at leastin part upon the image data of the implement.
 12. The agriculturalvehicle of claim 11, wherein the controller is further configured tooptimize the turning maneuver by minimizing a turning radius of theagricultural vehicle.
 13. The agricultural vehicle of claim 11, whereinthe controller is further configured to artificially limit a maximumturning angle of the agricultural vehicle to prevent interferencebetween the implement and the agricultural vehicle.
 14. The agriculturalvehicle of claim 13, wherein the implement comprises a drawbar connectedto the agricultural vehicle, wherein the controller is furtherconfigured to determine an angle of the drawbar relative to theagricultural vehicle depending at least in part upon the image data ofthe implement, wherein the controller is configured to artificiallylimit the maximum turning angle of the agricultural vehicle dependingupon the angle of the drawbar relative to the agricultural vehicle. 15.The agricultural vehicle of claim 13, wherein the implement comprises adrawbar connected to the agricultural vehicle, wherein the controller isfurther configured to determine an interference zone of the drawbar,wherein the controller is configured to artificially limit the maximumturning angle of the agricultural vehicle depending upon a position ofthe agricultural vehicle relative to the interference zone of thedrawbar.
 16. The agricultural vehicle of claim 13, further comprising asteering system operably connected to the controller, wherein thecontroller is further configured to determine and send a steer-limitoutput signal to the steering system so that the steering systemprevents the agricultural vehicle from turning beyond the maximumturning angle of the agricultural vehicle which was artificially limitedby the controller.
 17. The agricultural vehicle of claim 16, wherein thecontroller is further configured to automatically steer the agriculturalvehicle during the turning maneuver by way of the controllerautomatically controlling the steering system to minimize a turningradius of the agricultural vehicle and prevent interference between theimplement and the agricultural vehicle.
 18. The agricultural vehicle ofclaim 11, wherein the controller is configured to compare the image dataof the implement to a database of implements and match the implement toone implement of the database of implements in order to identify theimplement.
 19. The agricultural vehicle of claim 18, wherein theagricultural vehicle is part of a neural network comprising at least oneother agricultural vehicle, wherein the controller is operably connectedto a network which operably connects the agricultural vehicle to the atleast one other agricultural.
 20. The agricultural vehicle of claim 18,wherein the controller is configured to conduct a machine learningalgorithm to, at least partially, create the database of implements andto identify the implement.